Purpose: Cement as one of the major components of construction activities, releases a tremendous amount of CO 2 into atmosphere, resulting in adverse environmental impacts and high energy ...consumption. Increasing demand for CO 2 consumption has urged construction companies and decision makers to consider ecological efficiency affected by CO 2 consumption. Therefore, this research aims at developing a method capable of analyzing and assessing the Ecoefficiency determining factor in Iran's 22 local cement companies over 2015-2019.Design/Methodology/Approach: This research utilizes two well-known artificial intelligence approaches, namely optimization Data Envelopment Analysis (DEA) and machine learning algorithms at the first and second steps respectively to fulfill the research aim. Meanwhile, to find the superior model, CCR model, BBC model, and additive DEA models to measure the efficiency of decision processes are used. A proportional decreasing or increasing of inputs/outputs is the main concern in measuring efficiency which neglect slacks and hence, is a critical limitation of radial models. Thus, additive model by considering desirable and undesirable outputs, as a well-known DEA nonproportional and non-radial model, are utilized to solve the problem. Additive models measure efficiency via slack variables. Considering both input-oriented and output-oriented is one of the main advantages of additive model.Findings and Implications: After applying the proposed model, the Malmquist Productivity Index (MPI) is computed to evaluate the productivity of companies over 2015-2019. Although DEA is an appreciated method for evaluating, it fails to extract unknown information. Thus, machine learning algorithms plays an important role at this step. Association rules is used to extract hidden rules, and to introduce the three strongest rules. Finally, three data mining classification algorithms in three different tools have been applied to introduce the superior algorithm and tool. A new converting two-stage to single-stage model is proposed to obtain the eco-efficiency of the whole system. This model is proposed to fix the efficiency of a two-stage process and prevent the dependency on various weights. Converting undesirable outputs, and desirable inputs to final desirable inputs in a single-stage model to minimize inputs as well as turning desirable outputs to final desirable outputs in the single stage model to maximize outputs to have a positive effect on the efficiency of the whole process
In today's rapid changing world, systems are more complex than those in the past, and different techniques such as simulation must be used to analyse them. Due to random existent situations in most ...of systems, the random aspect of simulation plays a significant role in this regard. Thus, randomization can be considered in simulation models by using random numbers and random variates. This paper compares one of the algorithms of generating random variates named "uniform fractional part , with other algorithms in the area of random variates. The study shows that the performance of this algorithm is much better than others with respect to speed and accuracy. Finally, a number of suggestions to improve the performance of the mentioned algorithm will be presented. PUBLICATION ABSTRACT
In today's rapid changing world, systems are more complex than those in the past, and different techniques such as simulation must be used to analyse them. Due to random existent situations in most ...of systems, the random aspect of simulation plays a significant role in this regard. Thus, randomization can be considered in simulation models by using random numbers and random variates. This paper compares one of the algorithms of generating random variates named "uniform fractional part", with other algorithms in the area of random variates. The study shows that the performance of this algorithm is much better than others with respect to speed and accuracy. Finally, a number of suggestions to improve the performance of the mentioned algorithm will be presented.
In this article using Cuckoo Optimization Algorithm and simple additive weighting method the hybrid COAW algorithm is presented to solve multi-objective problems. Cuckoo algorithm is an efficient and ...structured method for solving nonlinear continuous problems. The created Pareto frontiers of the COAW proposed algorithm are exact and have good dispersion. This method has a high speed in finding the Pareto frontiers and identifies the beginning and end points of Pareto frontiers properly. In order to validation the proposed algorithm, several experimental problems were analyzed. The results of which indicate the proper effectiveness of COAW algorithm for solving multi-objective problems.
Constrained Nonlinear programming problems are hard problems, and one of the most widely used and common problems for production planning problem to optimize. In this study, one of the mathematical ...models of production planning is survey and the problem solved by cuckoo algorithm. Cuckoo Algorithm is efficient method to solve continues non linear problem. Moreover, mentioned models of production planning solved with Genetic algorithm and Lingo software and the results will compared. The Cuckoo Algorithm is suitable choice for optimization in convergence of solution
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